Genetic sequencing technologies are evolving at a rapid pace with major implications for research and clinical practice. In this review, the authors provide an updated overview of next-generation sequencing (NGS) and emerging methodologies. NGS has tremendously improved sequencing output while being more time and cost-efficient in comparison to Sanger sequencing. The authors describe short-read sequencing approaches, such as sequencing by synthesis, ion semiconductor sequencing, and nanoball sequencing. Third-generation long-read sequencing now promises to overcome many of the limitations of short-read sequencing, such as the ability to reliably resolve repeat sequences and large genomic rearrangements. By combining complementary methods with massively parallel DNA sequencing, a greater insight into the biological context of disease mechanisms is now possible. Emerging methodologies, such as advances in nanopore technology, in situ nucleic acid sequencing, and microscopy-based sequencing, will continue the rapid evolution of this area. These new technologies hold many potential applications for hematological disorders, with the promise of precision and personalized medical care in the future.

Ischemic limb injury can be broadly classified into arterial (absent pulses) and venous/microvascular (detectable pulses); the latter can be divided into two overlapping disorders-venous limb gangrene (VLG) and symmetrical peripheral gangrene (SPG). Both VLG and SPG feature predominant acral (distal) extremity ischemic necrosis, although in some instances, concomitant nonacral ischemia/skin necrosis occurs. Historically, for coagulopathic disorders with prominent nonacral ischemic necrosis, clinician-scientists implicated depletion of natural anticoagulants, especially involving the protein C (PC) system. This historical review traces the recognition of natural anticoagulant depletion as a key feature of nonacral ischemic syndromes, such as classic warfarin-induced skin necrosis, neonatal purpura fulminans (PF), and meningococcemia-associated PF. However, only after several decades was it recognized that natural anticoagulant depletion is also a key feature of predominantly acral ischemic microthrombosis syndromes-VLG and SPG-even when accompanying nonacral thrombosis is not present. These acquired acral limb ischemic syndromes typically involve the triad of (a) disseminated intravascular coagulation, (b) natural anticoagulant depletion, and (c) a localizing explanation for microthrombosis occurring in one or more limbs, either deep vein thrombosis (helping to explain VLG) or circulatory shock (helping to explain SPG). In most cases of VLG or SPG there are one or more events that exacerbate natural anticoagulant depletion, such as warfarin therapy (e.g., warfarin-associated VLG complicating heparin-induced thrombocytopenia or cancer hypercoagulability) or acute ischemic hepatitis ("shock liver") as a proximate factor predisposing to severe depletion of hepatically synthesized natural anticoagulants (PC, antithrombin) in the setting of circulatory shock.

Platelets are the smallest blood cells, numbering 150 to 350 × 109/L in healthy individuals. The ability of activated platelets to adhere to an injured vessel wall and form aggregates was first described in the 19th century. Besides their long-established roles in thrombosis and hemostasis, platelets are increasingly recognized as pivotal players in numerous other pathophysiological processes including inflammation and atherogenesis, antimicrobial host defense, and tumor growth and metastasis. Consequently, profound knowledge of platelet structure and function is becoming more important in research and in many fields of modern medicine. This review provides an overview of platelet physiology focusing particularly on the structure, granules, surface glycoproteins, and activation pathways of platelets.

Khorana score (KS) is an established risk assessment model for predicting cancer-associated thrombosis. However, it ignores several risk factors and has poor predictability in some cancer types. Machine learning (ML) is a novel technique used for the diagnosis and prognosis of several diseases, including cancer-associated thrombosis, when trained on specific diagnostic modalities. Consolidating the literature on the use of ML for the prediction of cancer-associated thrombosis is necessary to understand its diagnostic and prognostic abilities relative to KS. This systematic review aims to evaluate the current use and performance of ML algorithms to predict thrombosis in cancer patients. This study was conducted per Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Databases Medline, EMBASE, Cochrane, and ClinicalTrials.gov, were searched from inception to September 15, 2023, for studies evaluating the use of ML models for the prediction of thrombosis in cancer patients. Search terms "machine learning," "artificial intelligence," "thrombosis," and "cancer" were used. Studies that examined adult cancer patients using any ML model were included. Two independent reviewers conducted study selection and data extraction. Three hundred citations were screened, of which 29 studies underwent a full-text review, and ultimately, 8 studies with 22,893 patients were included. Sample sizes ranged from 348 to 16,407 patients. Thrombosis was characterized as venous thromboembolism (n = 6) or peripherally inserted central catheter thrombosis (n = 2). The types of cancer included breast, gastric, colorectal, bladder, lung, esophageal, pancreatic, biliary, prostate, ovarian, genitourinary, head-neck, and sarcoma. All studies reported outcomes on the ML's predictive capacity. The extreme gradient boosting appears to be the best-performing model, and several models outperform KS in their respective datasets.

Fibrin, described on a single-lens microscopy for the first time by Malpighi in 1666 and named by de Fourcroy, has been extensively studied by biochemists, biophysicists, and more recently by clinicians who recognized that fibrin is the major component of most thrombi. Elucidation of key reactions leading to fibrin clot formation in the 1950s and 1960s grew interest in the clinical relevance of altered fibrin characteristics. Implementation of scanning electron microscopy to image fibrin clots in 1947 and clot permeation studies in the 1970s to evaluate an average pore size enabled plasma clot characterization in cohorts of patients. Unfavorably altered fibrin clot structure was demonstrated by Blombäck's group in coronary artery disease in 1992 and in diabetes in 1996. Fifteen years ago, similar plasma fibrin clot alterations were reported in patients following venous thromboembolism. Multiple myeloma was the first malignant disease to be found to lead to abnormal fibrin clot phenotype in the 1970s. Apart from anticoagulant agents, in 1998, aspirin was first shown to increase fibrin clot permeability in cardiovascular patients. The current review presents key data on the rich history of fibrin research, in particular, those that first documented abnormal fibrin clot properties in a variety of human disease states, as well as factors affecting fibrin phenotype.